Doctor of Philosophy in Electrical Engineering
Sharif University of Technology, Tehran, Iran
Oct 2018 - July 2023
About me
Aref Einizade
I received my M.Sc. degree in Electrical Engineering (with a focus on Bioelectric Engineering) from the Sharif University of Technology, Tehran, Iran, in 2018. I also got my Ph.D. in 2023 in Electrical Engineering from the Sharif University of Technology by developing Graph Signal Processing (GSP) and Graph Machine Learning (GML) algorithms and their applications in biomedical (mostly the brain) data processing under the supervision of Prof. Sepideh Hajipour Sardouie.
Currently, I am a postdoctoral researcher at LTCI, Télécom Paris, Institut Polytechnique de Paris (IP-Paris), France, working on the intersection of GSP and Graph Neural Networks (GNNs) under the supervision of Prof. Jhony Giraldo and Prof. Fragkiskos D. Malliaros. My research interests are GSP, GML, image processing, matrix and tensor decompositions, machine learning, and deep learning algorithms.
Research Interests
Graph Machine Learning (GML)
Graph Signal Processing (GSP)
Matrix and Tensor Decompositions
Machine Learning / Deep Learning algorithms
Awards and Honors
1. Winning the HI! PARIS postdoctoral fellowship 2023.
2. Best Ph.D. Student, EE Department, Sharif University of Technology.
3. Top %1 in Graduate (and Ph.D.) national entrance exam.
4. Ranked 1st in Master of Science, Bioelectric Major, EE Department, Sharif University of Technology .
Resume
Education
Thesis: Subspace Identification and Graph Learning of Graph Signals: Application in Brain Signal Processing.
Master of Science in Electrical Engineering
Sharif University of Technology, Tehran, Iran
Oct 2016 - Sep 2018
Thesis: Iterative Pseudo Sparse Partial Least Square and its Higher-Order variant: Application to inference from high-dimensional biosignals.
Bachelor of Science in Electrical Engineering-Digital Systems
Sharif University of Technology, Tehran, Iran
Oct 2011 - Sep 2015
Thesis: Designing an application on android framework with JAVA that helps users control or manage electronic devices, and also implementation of it on AVR microcontroller and Bluetooth module using C++ in CodeVision.
Research/Job Experience
Postdoctoral researcher
LTCI, Télécom Paris, Institut Polytechnique de Paris (IP-Paris), France.
Oct 2023 - Present
Thesis: Learning Multi-domain Graphs from Data via Graph Machine Learning.
Teacher Assistant (TA)
LTCI, Télécom Paris, Institut Polytechnique de Paris (IP-Paris), France.
Jun 2024
the Source separation and Non-negative Matrix Factorization labs.
Co-Supervision of several B.Sc. students at Electrical Engineering
Sharif University of Technology, Tehran, Iran
Sep 2022 - Present
Teacher Assistant (TA) in selected courses
Sharif University of Technology, Tehran, Iran
Oct 2017 - Sep 2022
Deep Learning, Computer Vision, Tensor Decompositions in Signal Processing, EEG Signal Processing, Medical Image Processing, Medical Image Systems, Biomedical Signal and Image Processing Lab
EEG signal processing presentation at Sharif Neuroscience Symposium
Sharif University of Technology, Tehran, Iran
Jan 2020 - Feb 2020
Skills
Python
Matlab
C/C++
LATEX
95%
PyTorch
97%
Tensorflow
100%
Keras
100%
OpenCV
My work process
01
Expression of ideas
02
Literature Review
03
Checking available methods and approaches
04
Implementation
Publications
- Journal Papers
- Conference Papers
- Pre-prints
Journal Papers
1. Giraldo, J. H., Einizade, A., Todorovic, A., Castro-Correa, J. A., Badiey, M., Bouwmans, T., & Malliaros, F. D. (2024). “Higher-Order GNNs Meet Efficiency: Sparse Sobolev Graph Neural Networks”, IEEE Transactions on Signal and Information Processing over Networks.
2. Einizade, A., Giraldo, J. H., Malliaros, F. D., Sardouie, S. H. (2024). “Estimation of a Causal Directed Acyclic Graph Process using Non-Gaussianity”, Digital Signal Processing.
3. Einizade, A., Nasiri, S., Sardouie, S. H., Clifford, G. D. (2023). “ProductGraphSleepNet: Sleep staging using product spatio-temporal graph learning with attentive temporal aggregation.”, Neural Networks.
4. Einizade, A., Sardouie, S. H. (2023). “Learning product graphs from spectral templates.”, IEEE Transactions on Signal and Information Processing over Networks.
5. Einizade, A., Sardouie, S. H. (2023). “Iterative Pseudo-Sparse Partial Least Square and its Higher-Order variant: Application to inference from high-dimensional biosignals.”, IEEE Transactions on Cognitive and Developmental Systems.
6. Einizade, A., Sardouie, S. H. (2023). “Joint Graph Learning and Blind Separation of Smooth Graph Signals Using Minimization of Mutual Information and Laplacian Quadratic Forms.”, IEEE Transactions on Signal and Information Processing over Networks, 9, 35-47.
7. Einizade, A., Nasiri, S., Mozafari, M., Sardouie, S. H., Clifford, G. D. (2023). “Explainable automated seizure detection using attentive deep multi-view networks.”, Biomedical Signal Processing and Control, 79, 104076.
8. Einizade, A., Sardouie, S. H. (2022). “Robust blind separation of smooth graph signals using minimization of graph regularized mutual information.”, Digital Signal Processing, 132, 103792.
9. Einizade, A., Mozafari, M., Jalilpour, S., Bagheri, S., Sardouie, S. H. (2022). “Neural decoding of imagined speech from EEG signals using the fusion of graph signal processing and graph learning techniques.”, Neuroscience Informatics, 2(3), 100091.
10. Einizade, A., Sardouie, S. H. (2022). “A unified approach for simultaneous graph learning and blind separation of graph signal sources.”, IEEE Transactions on Signal and Information Processing over Networks, 8, 543-555.
11. Einizade, A., Sardouie, S. H., Shamsollahi, M. B. (2021). “Simultaneous graph learning and blind separation of graph signal sources.”, IEEE Signal Processing Letters, 28, 1495-1499.
12. Mijani, A. M., Einizade, A., Shamsollahi, M. B., Beyglou, B. T. (2020). “Cross-subject and crossparadigmlearning using convolutional neural network for P300 event-related potential detection.”, J Neurol Neurosci, 11(5), 329.
13. Einizade, A., Hajipour Sardouie, S. (2020). “Sparsification of the PLS Regression Algorithm using L2-Norm of Weighted Coefficients: Application in Emotion Recognition.”, Iranian Journal of Biomedical Engineering, 14(3), 221-233.
Conference Papers
1. Einizade, A., Malliaros, F. D., & Giraldo, J. H. (2024). “Continuous Product Graph Neural Networks.”, The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS).
2. Einizade, A., Mozafari, M., Sardouie, S. H., Nasiri, S., Clifford, G. (2020, December). “A deep learningbased method for automatic detection of epileptic seizure in a dataset with both generalized and focal seizure types.”, In 2020 IEEE Signal Processing in Medicine and Biology Symposium (SPMB) (pp. 1-6). IEEE.
3. Einizade, A., Mozafari, M., Rezaei-Dastjerdehei, M., Aghdaei, E., Mijani, A. M., & Sardouie, S. H. (2020, November). “Detecting ADHD children based on EEG signals using Graph Signal Processing techniques.”, In 2020 27th National and 5th International Iranian Conference on Biomedical Engineering (ICBME) (pp. 264-270). IEEE.
Pre-prints
1. Einizade, A., Malliaros, F. D., & Giraldo, J. H. (2024). “Spatiotemporal Forecasting Meets Efficiency: Causal Graph Process Neural Networks.”, Under Review at IEEE TNNLS.
2. Alizade, M. H., Einizade, A., & Giraldo, J. H. (2023). “Kernel-based Joint Multiple Graph Learning and Clustering of Graph Signals.”, arXiv e-prints, arXiv-2310.
Academic Activities
- Supervising Activities
- Teaching Activities
- Invited Reviewer
Supervising Activities
1. Omid Rostamabadi and Alireza Rafiee Sardoee, Bachelor Student at Sharif University of Technology. “Developing Large Scale Graph Learning Approach to Learn the Functional Brain Connectivity”.
2. Yasamin Medghalchi, Bachelor Student at Sharif University of Technology. “Combining Support Matrix Machines and Graph Learning Approaches to Improve the classification of EEG signals”.
Teaching Activities
1. • Teacher Assistant (TA) in the Source separation and Non-negative Matrix Factorization labs at Télécom Paris, Institut Polytechnique de Paris (IP-Paris).
2. Teacher Assistant (TA) in selected courses: Deep Learning, Computer Vision, Tensor Decompositions in Signal Processing, EEG Signal Processing, Medical Image Processing, Medical Image Systems, Biomedical Signal and Image Processing Lab.
3. Teaching fundamentals in Math and Physics for university entrance students.
Contact
Télécom Paris, Institut Polytechnique de Paris
Address